In A Nutshell
Play a key role in leading Giga’s data strategy, ensuring that Giga’s datasets, pipelines, and analytics products are accurate, open, actionable, and impactful.
Responsibilities
- Data Strategy: Develop and implement Giga’s comprehensive data strategy, defining the vision for data-driven decision-making and analytics innovation.
- Open-Source Data Management: Design and execute a plan to open-source Giga’s school geo-location and connectivity datasets, ensuring compliance with data quality and licensing standards.
- Data Governance & Quality: Establish and oversee data governance best practices, including data documentation, metadata management, and quality assurance processes using tools such as Datahub, Deltalake, and Great Expectations.
- Data Integration & Pipelines: Collaborate with engineers to design, maintain, and optimize robust, scalable, and automated data pipelines ensuring the integrity and timeliness of analytics outputs.
- Product Analytics: Build and manage analytics frameworks and dashboards (e.g., in Superset, Grafana, Mixpanel) for Giga’s digital products (such as Giga Maps and Giga Meter) to monitor adoption, performance, and impact.
- Network Data Partnerships: Act as a technical lead for data partnerships with Internet Service Providers (ISPs) and network partners, defining requirements and overseeing data integration with Giga’s monitoring systems.
- Advanced Analytics & Insights: Develop automated reports, visualizations, and analytical stories to provide actionable insights for internal teams, partners, and the public.
- Stakeholder Engagement: Represent Giga’s data initiatives to governments, private sector partners, and open-source communities, organizing data workshops and capacity-building sessions.
- Open Data Community Building: Work alongside the open-source community manager to engage contributors, manage data repositories, and drive community participation.
- Knowledge Sharing: Contribute to analytical blog posts, internal documentation, and communication materials to disseminate insights and best practices.
Skillset
- Advanced university degree (Master’s or higher) in Statistics, Data Analytics, Computer Science, or a related field is required.
- A first University Degree (Bachelor`s degree or equivalent) in a relevant field combined with 2 additional years of professional experience may be accepted in lieu of an Advanced University Degree.
- Minimum of 5 years of professional experience in data analytics, data engineering, or related field is required.
- Experience managing geo-spatial and/or internet network datasets and conducting product analytics is required.
- Hand-on experience with open-source analytical stacks such as Superset, Trino, QGIS, Kepler, Mapbox, Carto, PostgreSQL, and Dagster is required.
- Experience with Python and SQL for data analysis and automation is required.
- Experience implementing data governance and data quality frameworks using tools such as Datahub, Deltalake, or Great Expectations is required.